Pre Condition:

Learning:

Each team in the NBA has one goal at the end of the season, to hoist up the trophy from winning the championship. Naturally, teams that have the best players finish better than the other teams. If you are the General Manager of a team, you want to get the best players, hen they are at their best. Best, in this case, means in their prime. Players are in their prime years when they are performing at the highest level of their careers.

Its easy, build a team of players in their prime, and, you should have a good enough team to win the championship. So, how exactly should a GM tell if a players is in their prime?

Winnowing:

The data set I will use is a large set of all players in the NBA since 1950. Each player (row) in the data set has all their stats (columns). This data (https://www.kaggle.com/nathanlauga/nba-games) will not be biased. Its simply just a hugh data set of stats over the last 70 years.

Core:

Discover:

1) Task 1 - create a visualization that considers average points per game over the year and compare with age. The age(s) with the most PPG are the years they are in their prime. a) Why? To find a players prime based on PPG b) How? By a data visualization comparing average PPG with players age. c) What? Getting every players PPG/year over the span of their career. d) Where? Data set provided e) When? After Initial question e) Who? me!

1) Task 2 - create a visualization that considers field goal percentage over the year and compare with age. The age(s) with the highest FG% are the years they are in their prime. a) Why? To find a players prime based on FG% b) How? By a data visualization comparing average FG% with players age. c) What? Getting every players FG%/year over the span of their career. d) Where? Data set provided e) When? After Initial question e) Who? me!

Design

See Below.

Impliment

These visualization are directly mapped to my two tasks. They both show FG% and PPG based on a players age. They are both made with altair.

Deploy

Based on the visualizations above, I can observe that a players age has a very stong correlation on their PPG. That being said, can can conclude a players prime to be between ages 24-28. Also, FG% does not seem to vary with player age, "once a good shooter, always a good shooter"

Iterate

1) New Task - create a visualization that can answer the question: does a team with more players in their prime (highest PPG over career) win MORE games than other teams? a) Why? To find if teams with more prime players perform better. b) How? By a data visualization comparing teams prime players to teams wins. c) What? Getting number of players in their prime on each team, and see if that team wins more. d) Where? Data set provided e) When? After Initial question e) Who? me!

Analysis:

Reflect, Part I

My solution shows players have an age bracket where they perform at a higher level, in this case: points per game. We can see that there is in fact a bracket, and it is set at 24-28 years of age.

Reflect, Part II

My solution shows data visualization can in fact answer my target question: When are players in their scoring prime. It is very cool to see this, because you dont have to know anything about basketball or the dataset, the viewer can just look at the visualization and see when a player is in their scoring prime.